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Background    Escherichia coli  O157 (EcO157) infection has been recognized as an important global public health concern. But information on the prevalence of EcO157 in cattle at the global and at the wider geographical levels is limited, if not absent. This is the first meta-analysis to investigate the point prevalence of EcO157 in cattle at the global level and to explore the factors contributing to variation in prevalence estimates.    Methods  Seven electronic databases- CAB Abstracts, PubMed, Biosis Citation Index, Medline, Web of Knowledge, Scirus and Scopus were searched for relevant publications from 1980 to 2012. A random effect meta-analysis model was used to produce the pooled estimates. The potential sources of between study heterogeneity were identified using meta-regression.    Principal findings  A total of 140 studies consisting 220,427 cattle were included in the meta-analysis. The prevalence estimate of EcO157 in cattle at the global level was 5.68% (95% CI, 5.16–6.20). The random effects pooled prevalence estimates in Africa, Northern America, Oceania, Europe, Asia and Latin America-Caribbean were 31.20% (95% CI, 12.35–50.04), 7.35% (95% CI, 6.44–8.26), 6.85% (95% CI, 2.41–11.29), 5.15% (95% CI, 4.21–6.09), 4.69% (95% CI, 3.05–6.33) and 1.65% (95% CI, 0.77–2.53), respectively. Between studies heterogeneity was evidenced in most regions. World region (p<0.001), type of cattle (p<0.001) and to some extent, specimens (p = 0.074) as well as method of pre-enrichment (p = 0.110), were identified as factors for variation in the prevalence estimates of EcO157 in cattle.    Conclusion  The prevalence of the organism seems to be higher in the African and Northern American regions. The important factors that might have influence in the estimates of EcO157 are type of cattle and kind of screening specimen. Their roles need to be determined and they should be properly handled in any survey to estimate the true prevalence of EcO157.

Regional Variation in the Prevalence of E. coli O157 in Cattle: A Meta-Analysis and Meta-Regression